DATA: Dependency-Aware Task Allocation Scheme in Distributed Edge Clouds

Jaewook Lee, Haneul Ko, Joonwoo Kim, Sangheon Pack

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


To overcome the limitation of standalone edge cloud in terms of computing power and resource, a concept of distributed edge cloud has been introduced, where application tasks are distributed to multiple edge clouds for collaborative processing. To maximize the effectiveness of the distributed edge cloud, we formulate an optimization problem of task allocation to minimize the application completion time. To mitigate high complexity overhead in the formulated problem, we devise a low-complexity heuristic algorithm called dependency-aware task allocation (DATA) algorithm. Evaluation results demonstrate that DATA can reduce the application completion time up to by 15%-32% compared to conventional dependency-unaware task allocation schemes.

Original languageEnglish
Article number9079591
Pages (from-to)7782-7790
Number of pages9
JournalIEEE Transactions on Industrial Informatics
Issue number12
Publication statusPublished - 2020 Dec


  • Distributed edge cloud
  • heuristic algorithm
  • mixed integer nonlinear program (MINLP)
  • optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering


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